UX News
A look at what's going on in the field of user experience.
Designing for signals: how intent & instrumentation shape AI-powered experiences
, UX Collective - Medium
As AI mirrors how we design and learn, our role evolves from creating interfaces to defining the signals that shape intelligent experiences.A quick note before we dive in. This essay continues the thinking I introduced in From design to direction: bridging product design and AI thinking. While it is not required reading, it might give helpful context as I build on some of the ideas from that earlier exploration. Do not worry, I will be here when you return.Illustration for how signals will be key in a more generative experiential future.In my first thought piece, I discussed how AI concepts overlap with the work of product designers as we optimize across three key levels: the interfaces we aim to make frictionless, the journeys that help users find value, and the connection to the business outcomes we hope to achieve.
That work is becoming even more important today. As AI-driven and generative tools move into our day-to-day workflows, the experiences we design no longer stop at the interface. Interfaces can now generate, adapt, and learn from what users do next. The quality of those learning loops depends on the quality of the signals we build into them.
What do Figma’s updates mean for Design Systems?
, UX Collective - Medium
A shift towards token-first and AI-assisted systemsFigma releases updates at a pace that feels pretty overwhelming. A new feature drops, you learn about the feature, then integrate it into your workflow. But soon after, more features are released and your workflow feels outdated again…like it’s an endless enhancement cycle.
For many designers, especially ones who manage large Design Systems, it’s hard to find time (and energy) to understand which features actually matter and how each Figma update affects your day-to-day work.
Why you need design maturity in a product organisation, and how to get it
, UX Collective - Medium
An exploration of causes, costs and competitive advantages connected to design maturity in product organisationsHigh‑performing product organisations depend on maturity across all disciplines — design, product management, engineering, data, editorial, architecture. When one discipline is not being fully utilised, the whole organisation suffers, because maturity is systemic. But design maturity is sometimes misunderstood as a craft issue. Sometimes design is equated with usability. But true design maturity expands an organisation’s capacity to work well in uncertainty. So if you want to create the future, rather than just predict it, you need to find ways to achieve design maturity.
Design maturity is more than usabilityI’m a design leader, so this matters to me personally. But a lack of understanding and investment in design maturity matters to everyone in a product organisation. When one function is underutilised, the entire system suffers. IDEO defines design as “sensemaking + imagination”. It’s the reason design is such a valuable partner to product management — design extends sense-making into difference-making. Product management excels at sense-making. It synthesises data and combines analytical skills with empathy to make decisions and provide direction — ultimately holding accountability for the success of the product. But without design maturity, an organisation can lose out on the creativity and divergent thinking strengths of design. This comes with costs. McKinsey’s Business Value of Design (2018) found that design maturity correlates directly with financial and product performance.
What Is the Difference Between Ease and Satisfaction?
, MeasuringU
“Satisfaction” is used rather broadly in vernacular speech.
We can feel satisfied with a meal, a movie, or a moment.
How design leaders use OKRs to win user research budget
, UX Collective - Medium
How to get your team to stop seeing user research as an expense
Customer Needs: A Simple Guide
, UX Planet - Medium
Why do we care about what customers need?
Style Guide vs Design System: The One Mistake Killing Your Team’s Speed & Consistency
, UX Planet - Medium
A Guide for Intermediate and Advanced Designers
As designers progress in their careers, the tools and frameworks we use evolve from basic visual references to comprehensive ecosystems that drive product consistency and scalability. If you’re an intermediate or advanced designer, you’ve likely encountered both style guides and design systems, but do you truly understand their differences and when to use each?
New UX/UI + AI Design Tools You Need to Try!
, UX Planet - Medium
Photo by Shubham Dhage on UnsplashEvery month, UX/UI design evolves: new tools emerge that change familiar processes, automate routine tasks, and simplify interface creation. Autumn was no exception, and over the past few weeks, there have been releases that surprised even those who regularly follow new industry solutions.
In this review, I have compiled the most interesting UX/UI tools worth your attention.
How India’s Largest Payment App Fixed a Problem with Just a Plus Button
, UX Planet - Medium
A masterclass in micro-UX for designers who want to find and fix invisible frictionPicture this.You’re buying a few things from a local vendor. They tell you the final amount after adding everything on their side. Nothing wrong with that, but you still want to double-check before paying. Just a quick addition to be sure.
So you do what most people do. You open your payment app, switch to the calculator, add the numbers yourself, switch back, and re-enter the total. It’s not hard. It’s just a small break in focus that happens before you make an online payment.
Rake Weighting: How to Weight Survey Data with Multiple Variables
, MeasuringU
Having a representative sample is ideal when making inferences about your customer or user population. In practice, it can be difficult to recruit the right proportion of respondents, leaving your sample out of balance with the population.
One way to adjust for being off balance is to weight the data you collected to get the sample back into proportion with the population percentages (such as for variables like age, geographic region, or experience levels).
